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1 # Copyright (c) 2016 The WebRTC project authors. All Rights Reserved. | |
2 # | |
3 # Use of this source code is governed by a BSD-style license | |
4 # that can be found in the LICENSE file in the root of the source | |
5 # tree. An additional intellectual property rights grant can be found | |
6 # in the file PATENTS. All contributing project authors may | |
7 # be found in the AUTHORS file in the root of the source tree. | |
8 | |
9 """Displays statistics and plots graphs from RTC protobuf dump.""" | |
10 | |
11 from __future__ import division | |
12 from __future__ import print_function | |
13 | |
14 import collections | |
15 import sys | |
16 import matplotlib.pyplot as plt | |
kjellander_webrtc
2016/06/15 14:46:54
Imports should be grouped with the order being mos
aleloi
2016/06/16 11:15:28
Done.
| |
17 import misc | |
18 import numpy | |
19 import pb_parse | |
20 | |
21 | |
22 class RTPStatistics(object): | |
23 """Has methods for calculating and plotting RTP stream statistics.""" | |
24 | |
25 BANDWIDTH_SMOOTHING_WINDOW_SIZE = 10 | |
26 | |
27 def __init__(self, data_points): | |
28 """Initializes object with data_points and computes simple statistics. | |
29 | |
30 Computes percentages of number of packets and packet sizes by | |
31 SSRC. | |
32 | |
33 Args: | |
34 data_points: list of pb_parse.DataPoints on which statistics are | |
35 calculated. | |
36 | |
37 """ | |
38 | |
39 self.data_points = data_points | |
40 self.ssrc_frequencies = misc.normalize_counter( | |
41 collections.Counter([pt.ssrc for pt in self.data_points])) | |
42 self.ssrc_size_table = misc.ssrc_normalized_size_table(self.data_points) | |
43 self.bandwidth_kbps = None | |
44 self.smooth_bw_kbps = None | |
45 | |
46 def print_ssrc_info(self, ssrc_id, ssrc): | |
47 """Prints packet and size statistics for a given SSRC. | |
48 | |
49 Args: | |
50 ssrc_id: textual identifier of SSRC printed beside statistics for it. | |
51 ssrc: SSRC by which to filter data and display statistics | |
52 """ | |
53 filtered_ssrc = [point for point in self.data_points if point.ssrc | |
54 == ssrc] | |
55 payloads = misc.normalize_counter( | |
56 collections.Counter([point.payload_type for point in | |
57 filtered_ssrc])) | |
58 | |
59 payload_info = "payload type(s): {}".format( | |
60 ", ".join(str(payload) for payload in payloads)) | |
61 print("{} 0x{:x} {}, {:.2f}% packets, {:.2f}% data".format( | |
62 ssrc_id, ssrc, payload_info, self.ssrc_frequencies[ssrc] * 100, | |
63 self.ssrc_size_table[ssrc] * 100)) | |
64 print(" packet sizes:") | |
65 (bin_counts, bin_bounds) = numpy.histogram([point.size for point in | |
66 filtered_ssrc], bins=5, | |
67 density=False) | |
68 bin_proportions = bin_counts / sum(bin_counts) | |
69 print("\n".join([ | |
70 " {:.1f} - {:.1f}: {:.2f}%".format(bin_bounds[i], bin_bounds[i + 1], | |
71 bin_proportions[i] * 100) | |
72 for i in range(len(bin_proportions)) | |
73 ])) | |
74 | |
75 def choose_ssrc(self): | |
76 """Queries user for SSRC.""" | |
77 | |
78 if len(self.ssrc_frequencies) == 1: | |
79 chosen_ssrc = self.ssrc_frequencies[0][-1] | |
80 self.print_ssrc_info("", chosen_ssrc) | |
81 return chosen_ssrc | |
82 | |
83 for (i, ssrc) in enumerate(self.ssrc_frequencies): | |
84 self.print_ssrc_info(i, ssrc) | |
85 | |
86 while True: | |
87 chosen_index = int(misc.get_input("choose one> ")) | |
88 if 0 <= chosen_index < len(self.ssrc_frequencies): | |
89 return list(self.ssrc_frequencies)[chosen_index] | |
90 else: | |
91 print("Invalid index!") | |
92 | |
93 def filter_ssrc(self, chosen_ssrc): | |
94 """Filters and wraps data points. | |
95 | |
96 Removes data points with `ssrc != chosen_ssrc`. Unwraps sequence | |
97 numbers and timestamps for the chosen selection. | |
98 """ | |
99 self.data_points = [point for point in self.data_points if | |
100 point.ssrc == chosen_ssrc] | |
101 unwrapped_sequence_numbers = misc.unwrap( | |
102 [point.sequence_number for point in self.data_points], 2**16 - 1) | |
103 for (data_point, sequence_number) in zip(self.data_points, | |
104 unwrapped_sequence_numbers): | |
105 data_point.sequence_number = sequence_number | |
106 | |
107 unwrapped_timestamps = misc.unwrap([point.timestamp for point in | |
108 self.data_points], 2**32 - 1) | |
109 | |
110 for (data_point, timestamp) in zip(self.data_points, | |
111 unwrapped_timestamps): | |
112 data_point.timestamp = timestamp | |
113 | |
114 def print_sequence_number_statistics(self): | |
115 seq_no_set = set(point.sequence_number for point in | |
116 self.data_points) | |
117 print("Missing sequence numbers: {} out of {}".format( | |
118 max(seq_no_set) - min(seq_no_set) + 1 - len(seq_no_set), | |
119 len(seq_no_set) | |
120 )) | |
121 print("Duplicated packets: {}".format(len(self.data_points) - | |
122 len(seq_no_set))) | |
123 print("Reordered packets: {}".format( | |
124 misc.count_reordered([point.sequence_number for point in | |
125 self.data_points]))) | |
126 | |
127 def estimate_frequency(self): | |
128 """Estimates frequency and updates data. | |
129 | |
130 Guesses the most probable frequency by looking at changes in | |
131 timestamps (RFC 3550 section 5.1), calculates clock drifts and | |
132 sending time of packets. Updates `self.data_points` with changes | |
133 in delay and send time. | |
134 """ | |
135 delta_timestamp = (self.data_points[-1].timestamp - | |
136 self.data_points[0].timestamp) | |
137 delta_arr_timestamp = float((self.data_points[-1].arrival_timestamp_ms - | |
138 self.data_points[0].arrival_timestamp_ms)) | |
139 freq_est = delta_timestamp / delta_arr_timestamp | |
140 | |
141 freq_vec = [8, 16, 32, 48, 90] | |
142 freq = None | |
143 for f in freq_vec: | |
144 if abs((freq_est - f) / f) < 0.05: | |
145 freq = f | |
146 | |
147 print("Estimated frequency: {}kHz".format(freq_est)) | |
148 if freq is None: | |
149 freq = int(misc.get_input( | |
150 "Frequency could not be guessed. Input frequency (in kHz)> ")) | |
151 else: | |
152 print("Guessed frequency: {}kHz".format(freq)) | |
153 | |
154 for point in self.data_points: | |
155 point.real_send_time_ms = (point.timestamp - | |
156 self.data_points[0].timestamp) / freq | |
157 point.delay = point.arrival_timestamp_ms -point.real_send_time_ms | |
158 | |
159 def print_duration_statistics(self): | |
160 """Prints delay, clock drift and bitrate statistics.""" | |
161 | |
162 min_delay = min(point.delay for point in self.data_points) | |
163 | |
164 for point in self.data_points: | |
165 point.absdelay = point.delay - min_delay | |
166 | |
167 stream_duration_sender = self.data_points[-1].real_send_time_ms / 1000 | |
168 print("Stream duration at sender: {:.1f} seconds".format( | |
169 stream_duration_sender | |
170 )) | |
171 | |
172 arrival_timestamps_ms = [point.arrival_timestamp_ms for point in | |
173 self.data_points] | |
174 stream_duration_receiver = (max(arrival_timestamps_ms) - | |
175 min(arrival_timestamps_ms)) / 1000 | |
176 print("Stream duration at receiver: {:.1f} seconds".format( | |
177 stream_duration_receiver | |
178 )) | |
179 | |
180 print("Clock drift: {:.2f}%".format( | |
181 100 * (stream_duration_receiver / stream_duration_sender - 1) | |
182 )) | |
183 | |
184 total_size = sum(point.size for point in self.data_points) * 8 / 1000 | |
185 print("Send average bitrate: {:.2f} kbps".format( | |
186 total_size / stream_duration_sender)) | |
187 | |
188 print("Receive average bitrate: {:.2f} kbps".format( | |
189 total_size / stream_duration_receiver)) | |
190 | |
191 def remove_reordered(self): | |
192 last = self.data_points[0] | |
193 data_points_ordered = [last] | |
194 for point in self.data_points[1:]: | |
195 if point.sequence_number > last.sequence_number and ( | |
196 point.real_send_time_ms > last.real_send_time_ms): | |
197 data_points_ordered.append(point) | |
198 last = point | |
199 self.data_points = data_points_ordered | |
200 | |
201 def compute_bandwidth(self): | |
202 """Computes bandwidth averaged over several consecutive packets. | |
203 | |
204 The number of consecutive packets used in the average is | |
205 BANDWIDTH_SMOOTHING_WINDOW_SIZE. Averaging is done with | |
206 numpy.correlate. | |
207 """ | |
208 self.bandwidth_kbps = [] | |
209 for i in range(len(self.data_points) - 1): | |
210 self.bandwidth_kbps.append(self.data_points[i].size * 8 / | |
211 (self.data_points[i + | |
212 1].real_send_time_ms - | |
213 self.data_points[i].real_send_time_ms) | |
214 ) | |
215 correlate_filter = (numpy.ones( | |
216 RTPStatistics.BANDWIDTH_SMOOTHING_WINDOW_SIZE) / | |
217 RTPStatistics.BANDWIDTH_SMOOTHING_WINDOW_SIZE) | |
218 self.smooth_bw_kbps = numpy.correlate(self.bandwidth_kbps, correlate_filter) | |
219 | |
220 def plot_statistics(self): | |
221 """Plots changes in delay and average bandwidth.""" | |
222 plt.figure(1) | |
223 plt.plot([f.real_send_time_ms / 1000 for f in self.data_points], | |
224 [f.absdelay for f in self.data_points]) | |
225 plt.xlabel("Send time [s]") | |
226 plt.ylabel("Relative transport delay [ms]") | |
227 | |
228 plt.figure(2) | |
229 plt.plot([f.real_send_time_ms / 1000 for f in | |
230 self.data_points][:len(self.smooth_bw_kbps)], | |
231 self.smooth_bw_kbps[:len(self.data_points)]) | |
232 plt.xlabel("Send time [s]") | |
233 plt.ylabel("Bandwidth [kbps]") | |
234 | |
235 plt.show() | |
236 | |
237 | |
238 def main(): | |
239 if len(sys.argv) < 2: | |
240 print("Usage: python rtp_analyzer.py <filename of rtc event log>") | |
241 sys.exit(0) | |
242 | |
243 data_points = pb_parse.parse_protobuf(sys.argv[1]) | |
244 rtp_stats = RTPStatistics(data_points) | |
245 chosen_ssrc = rtp_stats.choose_ssrc() | |
246 print("Chosen SSRC: 0X{:X}".format(chosen_ssrc)) | |
247 | |
248 rtp_stats.filter_ssrc(chosen_ssrc) | |
249 print("Statistics:") | |
250 rtp_stats.print_sequence_number_statistics() | |
251 rtp_stats.estimate_frequency() | |
252 rtp_stats.print_duration_statistics() | |
253 rtp_stats.remove_reordered() | |
254 rtp_stats.compute_bandwidth() | |
255 rtp_stats.plot_statistics() | |
256 | |
257 if __name__ == "__main__": | |
258 main() | |
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